1. Field of the Invention
The present invention relates to an image encoding technique and, more particularly, to a technique of encoding high-resolution image data easily and efficiently.
2. Description of the Related Art
Conventionally, an image encoding technique has been proposed which includes a component for dividing an image into blocks each formed from m×n pixels and losslessly encoding each block and a component for performing lossy encoding, and outputs one of the encoding results as the ultimate encoded data of a block of interest.
In principle, this technique raises the compression ratio in, e.g., a natural image region where image quality degradation is relatively unnoticeable by selectively applying the lossy encoding method. In contrast, for a character, line, CG portion, and the like where image quality degradation is noticeable, visual image quality degradation is suppressed using the lossless encoding method.
To suppress image quality degradation and reduce the code amount, it is important to appropriately select the encoding method in each region. Japanese Patent Laid-Open No. 08-167030 is known as a method of selecting lossless or lossy encoding by referring to the information amount or the number of colors of losslessly encoded data.
Lossless encoding is often performed using a predictive coding technique or a run-length coding technique. Predictive coding obtains the predicted value of a pixel of interest from neighboring pixels, calculates a predictive error that is the difference between the predicted value and the actual pixel value of the pixel of interest, and encodes the predictive error. Run-length coding converts identical continuous pixel values into numerals indicating run lengths, thereby encoding image data. On the other hand, lossy encoding generally uses a transform encoding technique which converts image data into frequency domain data using DCT or wavelet transform and encodes coefficient values. For both the lossless and lossy encoding techniques, various kinds of contrivance have been proposed to attain higher compression performance by introducing more sophisticated calculations.
Along with the recent increase in the precision of image input/output devices, image data resolution is becoming higher. To quickly process high-resolution image data, hardware resources and process time more than before are necessary. For example, to cause an encoding apparatus for handling an image having a resolution of 1200 dpi to do encoding within the same time as an earlier apparatus for encoding a 600-dpi image, the internal calculation processing capability needs to be four times larger than before.
Since efficient lossless and lossy encoding processes require sophisticated calculation processing, there is demanded an image encoding technique capable of satisfying three conditions, i.e., compression performance, image quality, and calculation cost in balance.